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Ach, und kurz davor muss man noch Seilbahn fahren. Katherine Goble Johnson's Life. Disability and Japanese Mom Porn in relation to frailty: how much do they overlap? Jun 18, Accumulation of deficits as a proxy measure of aging. The association between hydroxyvitamin D concentration, physical performance and frailty status in older adults. Zipf G, Chiappa M, Porter KS, Ostchega Y, Lewis BG, Dostal J. Regarding objective 1 to Geile Alte Weiber Nackt the relationship between individual nutrition-related parameters and frailtymany Heisse Girls Ficken not all nutrition-related parameters—especially those related to self-reported intake—varied in relation to the degree of frailty. Nice feature J Am Med Dir Assoc. Moreover, a meta-analysis of RCTs [ 62 ] reported the benefit of daily vitamin D supplementation on muscle strength Huge h&period balance in older people.
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Am Freitag waren demgegenüber nur Dividendenwerte im Wert von ca. Der Sound wurde laut vieler empörter Forenuser auch runtergedreht. Es ist jetzt Uhr. Wo genau diese das Geld angelegt hat, ist als Staatsgeheimnis zu betrachten. 10/26/ · Nutritional status and individual nutrients have been associated with frailty in older adults. The extent to which these associations hold in younger people, by type of malnutrition or grades of frailty, is unclear. Our objectives were to (1) evaluate the relationship between individual nutrition-related parameters and frailty, (2) investigate the association between individual nutrition. Huge quantities of waste biomass are generated as agricultural and food industry by-products, explaining around 30% of global was quantified for each goat during a 24 h period. The system used for gas exchange quantification was based on an indirect calorimetric system designed for small ruminants. But when the program costs $ million, that's not a huge increase, especially considering how we could have been looking at a $ million or more increase next school year if the school list had expanded to 1, buildings. However, in districts like Cleveland Heights-University Heights, which have been hammered by vouchers, yesterday's.

Importantly too, nutrition management appears to work well, in both hospital and community settings, as part of multidimensional interventions that also include exercise, pharmacological treatment, and social support [ 28 , 29 , 30 , 31 ].

Despite these promising insights, the evidence about the relationship of nutrition-related parameters with frailty, and whether these associations hold in younger people and by type of malnutrition, is limited and inconsistent [ 32 , 33 , 34 , 35 ].

Further, the multiplicity of claims about which nutritional factors might be most important is a pragmatic obstacle to uptake [ 8 , 36 , 37 , 38 ].

This obscures how the relationship might arise, and where new interventions might best be targeted. In other contexts in which the impact of age-related adverse outcomes varies by which items are studied, it has been useful to study deficits in the aggregate [ 39 ], something which has been variably applied in nutrition studies [ 40 ].

To help improve the understanding of the relationship between frailty and nutrition, this study aims 1 to evaluate the relationship between individual nutrition-related parameters and frailty, 2 to investigate the effect of these parameters on mortality risk across levels of frailty, and 3 to examine whether combining nutrition-related parameters in an index predicts mortality risk across frailty levels.

NHANES is a series of publicly available, cross-sectional surveys focusing on the health and nutrition of non-institutionalized US residents [ 41 , 42 ].

For the purpose of this study, individuals with missing FI scores were excluded. The final sample included participants.

Mortality status was identified from the death certificate records from the National Death Index in December 31, , and survival time was counted from the date of the clinical examination to the death event.

Each participant signed written informed consent provided to participate. The NHANES protocol was approved by the institutional review board of the Centers for Disease Control and Prevention CDC.

As a matter of policy, our local Research Ethics Committee does not review secondary analyses of duly approved, publicly available data.

Of 84 nutrition-related parameters included in NHANES, 62 items had established cut points. Among them, 34 energy and nutrient intake items were estimated from dietary information recalled during the h period prior to the interview.

Five anthropometric measurements and 23 blood tests related to nutrition were collected with standard techniques. These cut points were taken from a standard textbook, the Dietary Reference Intake DRIs , published guidelines, and previous studies [ 11 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ].

We excluded from the FI all items related to dietary intake or nutritional status i. The FI score, the number of deficits present divided by the total deficits considered, ranges between 0 and 1, and a higher score is associated with higher frailty.

A nutrition index NI was constructed following the deficit accumulation approach [ 57 ] by combining the 41 nutrition-related parameters that were related with higher frailty: counting the number of nutritional deficits in an individual and dividing by the total deficits considered.

Low-density lipoprotein cholesterol LDL-c and subscapular skinfold were excluded from the NI due to high number of missing data: Abnormal values that were found to be protective for frailty associated with lower levels of frailty were also scored as 0 Table 5 in Appendix.

The NI score ranges between 0 and 1; an NI score of 0 represents full nutritional health, while a score of 1 represents complete nutritional deficits.

All percentages and mean values were weighted using the sampling weights provided by NHANES. All regression models were adjusted for potential covariates including age, sex, race, energy intake, educational level, marital status, employment status, smoking, and study cohort.

Models which included energy, energy per weight, dietary fiber per energy intakes, and NI as predictors were not adjusted for energy intake. Annual household income was not included as covariate due to missing data.

The statistical analysis was conducted using IBM SPSS Statistics for Windows, Version Armonk, NY: IBM Corp. When we stratified the sample by frailty, The weighted mortality rate was 6.

Regarding objective 1 to evaluate the relationship between individual nutrition-related parameters and frailty , many but not all nutrition-related parameters—especially those related to self-reported intake—varied in relation to the degree of frailty.

To summarize, frailty was associated with 19 nutrient intakes Fig. With regard to anthropometric measurements, only being overweight was significantly associated with lower frailty.

Association between abnormal nutritional-related parameters and frailty. HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; MCV, mean corpuscular volume.

All analyses were adjusted for age, sex, race, energy intake, educational level, marital status, employment status, smoking, and study cohort except for energy, energy per weight, and dietary fiber per energy which were not adjusted for energy intake.

Results related to the relationship of the nutrition-related parameters with mortality risk objective 2 are presented in Fig. Association between abnormal nutritional-related parameters and mortality across levels of frailty.

FI, frailty index. All analyses were adjusted for age, sex, race, energy intake, educational level, marital status, employment status, smoking, and study cohort except for energy and energy per weight which were not adjusted for energy intake.

This proportion decreased with higher frailty, from 7. The weighted mean NI score was 0. After adjusting the survival analysis additionally for the FI, the HR per 0.

When we examined the joint effect of nutrition and frailty status on mortality, we found a dose-response relationship Fig.

Percentage of participants in each level of nutritional index score by frailty level. The percentages are weighted.

Association between nutritional index and mortality across levels of frailty. FI, frailty index; NI, nutritional index. All analyses were adjusted for age, sex, race, educational level, marital status, employment status, smoking, and study cohort except for energy and energy per weight which were not adjusted for energy intake.

Combined effect of frailty and nutrition on mortality. All analyses were adjusted for age, sex, race, educational level, marital status, employment status, smoking, and study cohort.

This observational study aimed to improve our understanding of the relationship between frailty and nutrition. As expected, we found that the two are related.

Nevertheless, fewer than half were individually associated with higher mortality risk across frailty levels and their impact differed across levels of frailty objective 2.

Only low serum vitamin D significantly increased the mortality risk across all levels of frailty. Even so, when we combined the nutrition-related parameters, including those not significantly associated with mortality, the resulting NI strongly predicted mortality risk, especially among those with higher FI scores objective 3.

In short, overall, the results show that frailty and nutrition are related, and for the most part, unless people are in good health, poor nutritional status increases mortality in a dose-dependent fashion, independent of age, sex, marital status, and education.

Several features of these results require additional comment. Regarding the individual items, vitamin D plays an important role in both bone metabolism and non-bony tissue function including skeletal muscles which relate with function in elderly people [ 58 ].

Previous observational studies [ 59 , 60 ] including one using the NHANES III data [ 61 ] showed that serum vitamin D levels were correlated with frailty and all-cause mortality in older adults.

Moreover, a meta-analysis of RCTs [ 62 ] reported the benefit of daily vitamin D supplementation on muscle strength and balance in older people.

Concerning cognitive function, severe vitamin D deficiency was also correlated with visual memory decline [ 63 ].

The current study confirmed the association between low serum vitamin D levels and both frailty levels and mortality risk across levels of frailty, not only in older people but also in younger people.

According to World Health Organization WHO , the normal range of weight in healthy adults is defined by body mass index BMI or Quetelet index between Even so, human physiology and mortality risk factors change with ageing.

BMI alone may not be a good indicator of adiposity in this population and this has been widely demonstrated based on the obesity paradox seen in the older people [ 66 , 67 ].

The present study showed that obesity was associated with higher frailty but had no relationship with mortality. It is possible that body composition and weight change may be better predictors in older people than BMI.

Moreover, low triceps skinfold in people with 0. On the subject of phytochemicals, previous studies [ 68 , 69 ] showed that low serum carotenoids levels were associated with higher frailty.

The relationship between the amount of dietary carotenoid intakes and their serum levels in older adults should be explored further.

Recommending carotenoids-rich fruits and vegetables consumption could be the focus of dietary interventions to improve frailty status.

This study illustrates the virtue of considering deficit accumulation as a means of providing context in age-related disorders. Deficit accumulation indices can quantify those packages of age-associated problems [ 71 ] and have been used by our group and others in a variety of contexts to quantify the cumulative impact of brain MRI changes [ 72 ], social vulnerability measures [ 73 ], laboratory measures [ 74 ], and ageing biomarkers [ 75 ].

An NI, constructed using the deficit accumulation approach, was a stronger prediction of frailty and mortality risk than were single nutritional parameters.

This study, similarly to previous studies [ 76 , 77 ], highlights that the accumulation of small deficits, even those that may not result in clinically detectable problems, corresponds to the ability of the organism to respond and recover from stressors [ 78 ].

A recent report noted the benefit to considering 11 nutrition-related parameters in mortality prediction, but did not evaluate frailty [ 40 ].

The findings from that work do not contradict our key clinical message: patient management should reflect not just nutritional parameters that cross an illness threshold, but the overall nutritional status.

In addition, there appears to be some merit in broader modeling of the nutrition risk as part of age-related deficit accumulation [ 79 ].

For example, the doubling time of biomarker deficits appears to be longer than laboratory ones, which in turn are longer than clinical deficits [ 74 , 75 , 80 ], something which appears to reflect their relative connectivity as nodes in a network.

How the various types of nutritional deficits fit in this spectrum is of interest, with an initial hypothesis that their variable relationships with mortality might reflect their connectivity or other network properties.

Recent work suggests that information theory might help better analyse factors that influence the health trajectories of individuals [ 79 ], offering pragmatic new approaches to studying age-related disease [ 81 ].

Here, participants with low energy consumption for their body weight were more likely to be frail.

Lower than recommended calorie intake can cause malnutrition; high levels of frailty are common among malnourished people [ 8 ]. Weight loss can be caused not only by loss of fat but also by loss of muscle and bony mass [ 83 ].

On the other hand, weight gain leads to more fat mass than muscle mass in sedentary young individuals. The fat accumulation itself is associated with many health deficits, especially the metabolic syndrome and metabolic-related diseases.

Even so, how the metabolic syndrome and frailty interact in relation to mortality appears to change across the life course [ 84 ].

The causes of frailty may be different at each age group. For example, younger people may accumulate deficits due to a chronic condition whereas older people may accumulate deficits even when few comorbidities are present [ 85 ].

Similarly, nutritional problems are altered across the lifespan. For example, older people may require more protein and calcium intake than do younger people [ 45 , 86 ] whereas the requirement for iron typically declines after the menopause [ 52 ].

Here, we recognized this by using cutoff points of normal intake according to the recommendation for each age and gender group. Even so, the effect of abnormal nutrition on frailty can be different in each age group and future interventional studies need to investigate this.

We used publicly available data from NHANES, a large population-based study with a well-controlled and rigorous protocol.

We analysed a huge number of nutrition-related parameters. However, our data must be interpreted with caution: a Due to the cross-sectional design, the causal relationship between frailty and nutrition cannot be examined and the duration of exposure to each parameter cannot be explored.

The absence of longitudinal data also makes it difficult to discern age from period and cohort effects.

Our data do however demonstrate that both frailty and nutritional deficiencies can be detected at all adult ages. Nutritional deficiencies, at least in the aggregate, can also be seen more commonly at higher ages and with frailty, and increase the lethality of frailty.

Here, for similar levels of deficit accumulation, at all ages, impaired nutrition reduced survival in people whose FI score were higher than 0. This study revealed that most nutritional parameters were related with frailty, but the impact of individual parameters on mortality differed across levels of frailty.

Only low vitamin D was associated with higher levels of frailty and higher risk for mortality across all levels of frailty.

The combined effect of frailty and nutrition deficits had the most impact on mortality risk. Balanced nutritional interventions appear to be reasonable approaches to remediating frailty.

Further studies are needed to examine the impact of nutritional interventional studies on frailty levels and to evaluate whether the number of nutritional deficits relates to other health outcomes such as hospitalization, institutionalization, and quality of life.

The original article [1] contained an error whereby Table 5 within the Appendix is presented incorrectly. This error has now been corrected and Table 5 is presented appropriately.

Lutz W, Sanderson W, Scherbov S. The coming acceleration of global population ageing. Ferrucci L, Giallauria F, Guralnik JM.

Epidemiology of aging. Radiol Clin N Am. Yazdanyar A, Newman AB. The burden of cardiovascular disease in the elderly: morbidity, mortality, and costs.

Clin Geriatr Med. Saad MA, Cardoso GP, Martins Wde A, Velarde LG, Cruz Filho RA. Prevalence of metabolic syndrome in elderly and agreement among four diagnostic criteria.

Arq Bras Cardiol. Plassman BL, Langa KM, Fisher GG, Heeringa SG, Weir DR, Ofstedal MB, et al. Prevalence of dementia in the United States: the aging, demographics, and memory study.

Gheno R, Cepparo JM, Rosca CE, Cotten A. Musculoskeletal disorders in the elderly. J Clin Imaging Sci. Hubbard RE, Theou O. Frailty: enhancing the known knowns.

Age Ageing. Lorenzo-Lopez L, Maseda A, de Labra C, Regueiro-Folgueira L, Rodriguez-Villamil JL, Millan-Calenti JC.

Nutritional determinants of frailty in older adults: a systematic review. BMC Geriatr. Muscedere J, Waters B, Varambally A, Bagshaw SM, Boyd JG, Maslove D, et al.

The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. Walters K, Frost R, Kharicha K, Avgerinou C, Gardner B, Ricciardi F, et al.

Home-based health promotion for older people with mild frailty: the HomeHealth intervention development and feasibility RCT.

Health Technol Assess. Blodgett JM, Theou O, Howlett SE, Rockwood K. A frailty index from common clinical and laboratory tests predicts increased risk of death across the life course.

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Stochastic Scalper for ThinkorSwim. Thread starter RickK Start date Aug 15, RickK Member. Hey All, Not sure if anyone has ever put this up, but I know that it has been around for quite some time.

I found it a long time ago on FunWithThinkscript. It's called Stochastic Scalper and I don't know who has taken credit for designing it I've been hot and cold on it for a long time I've included an image, the code which I liberally modified the "instructions"[if you want to call it that Would love to see some dialog on this to see what kind of results, if any, others are getting.

Also, if there is anyone that can convert this code to Tradingview pinescript, that would be awesome! I trade with Tradovate mostly now and chart using Tradingview because I got tired of TOS locking up, bogging down and just plain stopping for minutes at a time Stochastic Scalper hint: Stochastic Scalper - unattributed - I think it was originally designed for forex trading on MT4 Modifications to hints info done by RickKennedy, member usethinkscript.

INFO: This is designed to give short aggregation Signals 1 to 5 min. When used on a single chart, scalp when both lines agree green lines long, red lines short.

Best situation is when both lines agree on the 1m chart and both lines agree on the 5m chart Using the two chart method is usually a very high probability trade.

The white line is pure price scaled to the Stochastic range. Note: I have turned off the linear regression lines as I didn't feel that they really added anything, for me.

Likewise, I have turned off its chart labels that said "CHART TREND UP", "CHART TREND DOWN". Also I changed the labels from "BUY" to "BULLISH" and "SELL" to "BEARISH" and "SQUEEZE" to "SQZ" Yellow Triangles at the top of indicator show volume in the 30 percentile for that Volume Period or above.

When a light blue square appears on the white price line, this indicates divergence between price and the stochastic lines. A reversal could be coming.

Labels are used for trading signals. Added at the end of the script is a new bit of code that will display a heat map line at the top of the indicator green when both stochastic lines are green, red when both stochastic lines are red, and white when the lines are not the same.

Lastly, there is a section of code that I have turned off which allows the indicator to assign colors to the candles on the chart.

I couldn't figure out the use, so I commented it out Finally, there is a bit of complimentary code a separate indicator that will display the results of Stochastic Scalper on your watchlist.

This works for 1m and 5m. Nice feature Oh, I forgot to mention. You might want to play with the settings. Currently I am using it with a 10,6,60 setting on the short term chart and 6,6,60 on the longer term chart.

Advice: look for the lines to correlate on the longer term chart, then look for the lines to coincide on the short term chart.

Good luck! NaN; vP. SetPaintingStrategy PaintingStrategy. Mar 1, Apr 6, Aug 8, Written by Democrat David WIlmont Meant that California, Utah, and New Mexico would be closed to slavery forever.

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Jan 29, Mar 20, Harriet Beecher Stowe is the author of "Uncle Tom's Cabin" Purpose of novel: to bring awareness of the horror inacted in slavery Novel states that slavery was not only a political problem, but also a moral problem 1 million copies sold in middle of Northern abolitionists increased their protest AGAINST the Fugitive Slave Act Southerns did not like the novel due to the attack on the south as a whole Gave birth to a heated debate.

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McClellan SECOND BATTLE Aug , North - led by General John Pope lost 10, South - led by General Robert E. Lee, lost 1, South Won. Nov 19, Was a military plan designed by Winfield Scott.

Emphasized the blockade of the sourthern ports and called for an advance down the missisippi river to cut the south in two. Make south run out of supplies.

Sep 17, General Robert E.

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